Sensor fault detection and isolation for wind turbines based on subspace identification and Kalman filter techniques

Abstract

This paper aims at the blade root moment sensor fault detection and isolation issue for three-bladed wind turbines with horizontal axis. The underlying problem is crucial to the successful application of the individual pitch control system, which plays a key role for reducing the blade loads of large offshore wind turbines. In this paper, a wind turbine model is built based on the closed loop identification technique, where the wind dynamics is included. The fault detection issue is investigated based on the residuals generated by dual Kalman filters. Both additive faults and multiplicative faults are considered in this paper. For the additive fault case, the mean value change detection of the residuals and the generalized likelihood ratio test are utilized respectively. For multiplicative faults, they are handled via the variance change detection of the residuals. The fault isolation issue is proceeded with the help of dual sensor redundancy. Simulation results show that the proposed approach can be successfully applied to the underlying issue.

An advanced robust fault-tolerant tracking control for a doubly fed induction generator with actuator faults

“…More recently, many studies dealing with the problem of FTC systems have been designed for wind energy conversion systems (WECSs) [18][19][20][21][22][23][24][25][26][27][28]. In [18] an extended state observer-based AFTC scheme was presented, which provides an estimation of system states and fault signals for an offshore WT represented by linear parameter-varying descriptor systems.…”

“…In [19,20], the authors presented a robust approach for designing a FTC in order to stabilize nonlinear systems affected by sensor faults. In [21,22] a FTC scheme for WECSs was improved efficiently to deal with the problems of disturbance rejection and robust stabilization. In [23,24], the authors presented a FTC scheme for WECs described by T-S fuzzy models with sensor faults using a T-S fuzzy observer to achieve maximization of the power extraction from the generator.…”

Fault Diagnosis and Fault-Tolerant Control of Wind Turbines via a Discrete Time Controller with a Disturbance Compensator

“…Thus, WT pitch sensors and actuators are often the topic of the FDI and FTC research focus. For example, an H-infinity-based FDI technique to detect and estimate the magnitude of blade bending moment sensor and pitch actuator faults is given in [23]; blade root bending measurements are used to detect pitch misalignment in [24]; model-based and system identification techniques are used for pitch actuator faults in [25]; a technique for detecting additive and multiplicative actuator faults is developed in [26]; FTC in the case of faulty blade load measurements is implemented in [27].…”

Response analysis and comparison of a spar-type floating offshore wind turbine and an onshore wind turbine under blade pitch controller faults

“…Diagnosis and faulttolerant control methodologies have been applied in offshore engineering area by Fang, Blanke and Leira (2013) [8], where the safety of structural element is in high concern. Faults in the blade root bending moment strain gauges was simulated for a wind turbine with an individual pitch controller [9]. Active diagnosis was employed to isolate bending moment and pitch sensor faults by Brath, Dalsgaard and Blanke (2011) [10].…”